Latest AI and machine learning research in domestic violence for healthcare professionals.
BACKGROUND: Rib fractures are present in 10%-15% of thoracic trauma cases but are often missed on chest radiographs, delaying diagnosis and treatment. Artificial intelligence (AI) may improve detection and triage in emergency settings. OBJECTIVE: This study aims to evaluate diagnostic accuracy, processing speed, and technical feasibility of an artificial intelligence-assisted rib fracture detectio...
BACKGROUND: Physical frailty and cognitive frailty are increasingly recognized as critical geriatric syndromes among older adults with diabetes, contributing to adverse outcomes such as disability, hospitalization, and mortality. Early identification of individuals at high risk is therefore essential for timely prevention and intervention. Although a growing number of prediction models have been d...
Traditional statistical methods have limitations when dealing with high-dimensional, small-sample data. Deep learning methods have attracted widesprea...
Sepsis is a complex systemic inflammatory syndrome that currently lacks stable and specific biomarkers. Multi-omics integration combined with machine ...
In recent years, artificial intelligence (AI) has rapidly advanced in the field of oral medicine, with applications extending across disease screening...
BACKGROUND: Artificial intelligence (AI) chatbots are technologies that facilitate human-computer interaction through communication in a natural langu...
Artificial intelligence (AI) and deep learning (DL) are transforming cancer research and clinical care, with histopathology playing a central role in ...
Long-Term Care (LTC) in Canada faces persistent challenges in quality, staffing, and accountability. InterRAI assessment instruments, used nationally ...
Coronary computed tomography angiography (CCTA) has evolved into a key non-invasive tool for evaluating coronary artery disease, offering high sensiti...
OBJECTIVES: To assess the performance of a reasoning large language model (LLM) in identifying medication errors in medical incident reports. MATERIAL...
Explainability is crucial for establishing user trust in Artificial Intelligence (AI), particularly within safety-critical domains such as Air Traffic...
BACKGROUND: Delayed admission to the intensive care unit (ICU) after trauma can lead to tripling of in-hospital mortality. Accurate ICU resource predi...
BACKGROUND: Alzheimer's disease (AD) and dementia pose a significant clinical and economic burden globally. Early diagnosis and intervention can poten...
INTRODUCTION: Mental health problems constitute a significant global health challenge due to their rising prevalence and substantial treatment gap. Di...
Glaucoma is the leading cause of irreversible blindness worldwide with heterogeneous progression rates. Artificial Intelligence (AI) may enable accura...
BACKGROUND: Massive transfusion protocols are established in-hospital practices for managing haemorrhagic shock, yet critical bleeding accounts for up...
OBJECTIVES: This paper presents an experimental numerical method for modeling and analyzing stochastic systems. For this purpose, various machine pred...
BACKGROUND: This study aimed to demonstrate the feasibility of using computer vision (CV) to unobtrusively extract body motion metrics from videos of ...
OBJECTIVES: To evaluate the diagnostic interchangeability of DL-enhanced accelerated lumbar (L)-spine magnetic resonance imaging (MRI) with convention...
BACKGROUND. Insights into the nature of false-positive findings flagged by contemporary mammography artificial intelligence (AI) systems could inform ...